Staff

Structure

Lectures

Tue 10 AM – Chemistry Lecture Theatre 1

Wed 11 AM – Chemistry Lecture Theatre 3

Tutorials

Self-guided sessions (1 hour), to be completed before the week’s lab.

Labs

All labs are held in the South Eveleigh Precinct (more on this later):

• Thursday 9 am – 12 pm
• Friday 10 am – 1 pm, 2 pm – 5 pm

Attendance

• Mandatory for labs, 80% minimum required.
• Lecture attendance is highly recommended, but not compulsory.
• Lecture recordings capture slides and audio only. You will miss out on important discussions and informal feedback.

Assessments

library(gt)
assessments <- data.frame(
    Assessment = c("Project 1", "Project 2", "Project 3", "Canvas Quizzes", "Final exam"),
    Weight = c(10, 20, 20, 5, 45),
    Due = c("Week 5", "Week 10", "Week 13", "Weekly", "TBA"),
    Description = c("Report -- Describing data", "Report -- Analysing experimental data", "Presentation -- Modeling multivariate data (Topics 7 to 12)", "Weekly quizzes", "2 hours, Multiple Choice Questions + Short Answers")
)
gt::gt(assessments) # will enhance this if there's time

Biomedical Building

Credit: Michael Wheatland

Directions

Buses

Courtesy buses are available:

• Best option is to take the bus from Fisher Library to Redfern Station, then walk to the precinct (through the new station platform as “local traffic”).
• Alternatively, direct buses are available – but less frequent.

Driving

Free parking is available around Henderson Road, but it is extremely crowded. We do not recommend driving to the precinct.

Walking

Learn, so you can…

Attend lectures

Attending a lecture is not the same as watching a recording…

• You can ask questions and interact with your peers.
• Your lecturer actively adjusts the pace/conten based on your informal feedback (e.g. confused looks, Google polls).
• If you don’t understand something, there is a good chance that you can address it before the next lecture or lab.

Put in the hours

• This is a 6 credit point unit, which means that you are expected to spend 120 – 150 hours in total, including exam prep time (~10 h per week)!
• Practice makes perfect. Tutorials and Labs help you apply the concepts you learn in lectures – complete all the exercises, and practice with the bonus questions provided.

Ask questions

• Ed is the best place to ask questions. We are way more responsive on Ed than on email.
• We are open to the use of AI tools (including LLMs like ChatGPT) to help you answer questions about code… but don’t use them to cheat yourself out of learning.
• We have drop-in sessions, where you can jump in and have a chat on Zoom. We will announce the schedule on Ed.

By the end of this course, we want you to be able to:

• LO1 demonstrate proficiency in designing sample schemes and analysing data from them using R.
• LO2 describe and identify the basic features of an experimental design: replicate, treatment structure and blocking structure.
• LO3 demonstrate proficiency in the use or the statistical programming language R to apply an ANOVA and fit regression models to experimental data.
• LO4 demonstrate proficiency in the use or the statistical programming language R to use multivariate methods to find patterns in data.
• LO5 interpret the output and understand conceptually how its derived of a regression, ANOVA and multivariate analysis that have been calculated by R.
• LO6 write statistical and modelling results as part of a scientific report.
• LO7 appraise the validity of statistical analyses used publications.

Thanks!

Questions?

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